MAE_Data_Analysis
Michael Melville
2024-09-23
Load Necessary Libraries
Data Import
See GitHub_Export/Documentation for information on provided data.
## X Sub_ID Cond Avg_RPE Avg_HR SD_HR Max_HR Min_HR
## 1 1 1.1 Control 6.000000 73.06299 5.451750 87 63
## 2 2 1.2 Light 10.727273 106.34472 3.390666 114 98
## 3 3 1.3 Vigorous 16.818182 144.58533 4.232497 153 131
## 4 4 2.1 Vigorous 12.909091 152.13833 3.207753 158 145
## 5 5 2.2 Control 6.000000 88.95515 3.435594 101 81
## 6 6 2.3 Light 8.818182 116.47595 2.769795 126 108
## Percentage_Time_In_Zone Avg_Lower_THR Avg_Upper_THR HR_reserve
## 1 NA NA NA 128.5
## 2 0.9154472 100.55 112.115 128.5
## 3 0.8245614 139.10 150.665 128.5
## 4 0.9083333 145.98 156.627 118.3
## 5 NA NA NA 118.3
## 6 0.9568823 110.49 121.137 118.3
## Age_Predict_Max_HR SD_RPE Mean_Percent_HRR SD_Percent_HRR
## 1 190.5 0.0000000 8.609332 4.242607
## 2 190.5 1.1037127 34.509506 2.638650
## 3 190.5 0.9816498 64.268737 3.293772
## 4 193.3 0.3015113 65.205692 2.711541
## 5 193.3 0.0000000 11.796407 2.904137
## 6 193.3 0.4045199 35.059978 2.341331
## Accuracy_Response_Trials Accuracy_All_Trials No_Response Max_RT Min_RT
## 1 0.5789474 0.55 1 3.690534 1.1105052
## 2 0.8000000 0.80 0 2.627786 1.1844439
## 3 0.9000000 0.90 0 3.536698 1.5426400
## 4 0.9500000 0.95 0 2.520927 1.3734756
## 5 0.8500000 0.85 0 3.058130 1.0881356
## 6 0.9000000 0.90 0 2.148315 0.8554969
## Mean_RT High_Confidence_Hit Low_Confidence_Hit Low_Confidence_Miss
## 1 2.425303 9 2 2
## 2 1.852897 16 0 0
## 3 2.197293 17 1 1
## 4 2.063796 18 1 1
## 5 1.709206 14 3 0
## 6 1.414585 16 2 2
## High_Confidence_Miss HCH_percent LCH_percent LCM_percent HCM_percent
## 1 6 0.4736842 0.1052632 0.1052632 0.3157895
## 2 4 0.8000000 0.0000000 0.0000000 0.2000000
## 3 1 0.8500000 0.0500000 0.0500000 0.0500000
## 4 0 0.9000000 0.0500000 0.0500000 0.0000000
## 5 3 0.7000000 0.1500000 0.0000000 0.1500000
## 6 0 0.8000000 0.1000000 0.1000000 0.0000000
## Seed RawScore ItmCnt DateFinished Computed.Score
## 1 41.51562 20 24 44515.43 9.61
## 2 299.50000 20 24 44517.40 9.09
## 3 305.84375 19 24 44522.40 9.88
## 4 305.45312 20 24 44529.43 9.38
## 5 39.46875 20 24 44531.41 9.47
## 6 39.15625 20 24 44538.41 9.49
## Uncorrected.Standard.Score Age.Corrected.Standard.Score
## 1 113 116
## 2 108 99
## 3 116 127
## 4 111 103
## 5 112 108
## 6 112 108
## National.Percentile..age.adjusted. Fully.Corrected.T.score Appointment_Number
## 1 85 59 1
## 2 48 47 2
## 3 96 68 3
## 4 57 51 1
## 5 71 55 2
## 6 71 55 3
## pre_cc_mean pre_CE_mean pre_CO_mean pre_OE_mean post_CC_mean post_CE_mean
## 1 796.4958 783.5385 744.7333 NA 779.9412 979.1818
## 2 797.4454 679.1250 839.8500 NA 786.5378 946.1250
## 3 808.3077 764.4545 827.7059 895.5 800.7650 945.0000
## 4 856.0084 858.6667 848.7083 1181.0 858.2616 985.3333
## 5 835.9153 772.8571 831.9048 1276.0 834.4703 899.5714
## 6 783.9328 727.7500 785.5000 NA 780.8992 882.7500
## post_CO_mean post_OE_mean commission_rate commission_rate_q1
## 1 850.8889 NA 0.40625 0.1428571
## 2 851.7619 NA 0.25000 0.0000000
## 3 855.0000 662 0.34375 0.2857143
## 4 823.2692 NA 0.09375 0.1428571
## 5 820.0909 1084 0.21875 0.1428571
## 6 786.8000 NA 0.12500 0.0000000
## commission_rate_q2 commission_rate_q3 commission_rate_q4 omission_rate
## 1 0.4 0.750 0.2857143 0.000000000
## 2 0.4 0.250 0.2857143 0.000000000
## 3 0.4 0.250 0.4285714 0.007490637
## 4 0.1 0.125 0.0000000 0.003745318
## 5 0.3 0.250 0.1428571 0.003745318
## 6 0.2 0.000 0.2857143 0.000000000
## omission_rate_q1 omission_rate_q2 omission_rate_q3 omission_rate_q4 meanRT
## 1 0.00000000 0 0.00000000 0 792.9326
## 2 0.00000000 0 0.00000000 0 796.4494
## 3 0.02941176 0 0.00000000 0 808.7094
## 4 0.00000000 0 0.01492537 0 856.2744
## 5 0.00000000 0 0.01492537 0 835.9323
## 6 0.00000000 0 0.00000000 0 782.9775
## meanRT_q1 meanRT_q2 meanRT_q3 meanRT_q4 STD_RT STD_RT_q1 STD_RT_q2
## 1 752.4559 829.1538 801.4179 790.3881 117.44406 92.57356 122.17230
## 2 807.2794 778.9538 803.4328 795.4478 112.66725 93.16265 128.62244
## 3 791.3485 815.6308 838.9403 788.8657 126.92259 93.93263 125.66306
## 4 819.0147 870.9231 912.2273 824.7612 94.49642 72.27322 85.49768
## 5 824.5735 795.6308 892.4848 830.8507 95.27931 93.62267 65.09718
## 6 772.0441 805.2923 746.0448 809.3582 78.60183 65.80760 66.77077
## STD_RT_q3 STD_RT_q4 CV_RT CV_RT_q1 CV_RT_q2 CV_RT_q3 CV_RT_q4
## 1 138.94616 100.25527 0.1481136 0.12302855 0.14734575 0.1733754 0.12684310
## 2 128.03873 97.16158 0.1414619 0.11540323 0.16512203 0.1593646 0.12214703
## 3 137.48971 140.90970 0.1569446 0.11869945 0.15406857 0.1638850 0.17862318
## 4 99.13795 89.45798 0.1103576 0.08824410 0.09816904 0.1086768 0.10846531
## 5 109.15314 82.17097 0.1139797 0.11354071 0.08181833 0.1223025 0.09889980
## 6 97.23159 63.41917 0.1003884 0.08523813 0.08291494 0.1303294 0.07835736
## error_rate error_rate_q1 error_rate_q2 error_rate_q3 error_rate_q4
## 1 0.04347826 0.01333333 0.05333333 0.08000000 0.02702703
## 2 0.02675585 0.00000000 0.05333333 0.02666667 0.02702703
## 3 0.04347826 0.05333333 0.05333333 0.02666667 0.04054054
## 4 0.01337793 0.01333333 0.01333333 0.02666667 0.00000000
## 5 0.02675585 0.01333333 0.04000000 0.04000000 0.01351351
## 6 0.01337793 0.00000000 0.02666667 0.00000000 0.02702703
## mean_trial_length dprime criterion Overall.Accuracy Total.Trials
## 1 801.1833 3.136054 1.3308249 0.8402778 144
## 2 801.1700 3.573342 1.1121810 0.8819444 144
## 3 801.0800 2.835082 1.0152907 0.8819444 144
## 4 801.1600 3.992217 0.6780977 0.9166667 144
## 5 804.5300 3.450628 0.9488922 0.8680556 144
## 6 805.3367 4.049201 0.8742512 0.8888889 144
## Total.Trials.with.Response Total.Correct.Trials Lure.count Foil.count
## 1 136 121 23 93
## 2 142 127 23 95
## 3 142 127 23 95
## 4 142 132 23 96
## 5 144 125 24 96
## 6 144 128 24 96
## Target.count Average.Response.Time Average.RT.L Average.RT.F Average.RT.T
## 1 20 1143.3596 1278.109 1033.7710 1497.985
## 2 24 1077.9169 1238.426 997.4947 1242.433
## 3 24 1077.9169 1238.426 997.4947 1242.433
## 4 23 1300.7063 1353.713 1287.9927 1300.765
## 5 24 988.5486 1095.612 928.2656 1122.617
## 6 24 855.3549 1030.025 774.8458 1002.721
## Average.RT.when.Correct TO_rate TS_rate TN_rate LO_rate LS_rate
## 1 1118.1570 0.9000000 0.10000000 0 0.2173913 0.7826087
## 2 1042.6780 0.9166667 0.08333333 0 0.2173913 0.7391304
## 3 1042.6780 0.9166667 0.08333333 0 0.2173913 0.7391304
## 4 1298.4053 1.0000000 0.00000000 0 0.3043478 0.6521739
## 5 966.5344 0.9166667 0.08333333 0 0.4166667 0.5000000
## 6 828.1523 1.0000000 0.00000000 0 0.3333333 0.5416667
## LN_rate FO_rate FS_rate FN_rate NR_rate L3O_rate L3S_rate
## 1 0.00000000 0.03225806 0.05376344 0.9139785 0.05555556 0.0000000 1.0000000
## 2 0.04347826 0.00000000 0.07368421 0.9263158 0.01388889 0.0000000 1.0000000
## 3 0.04347826 0.00000000 0.07368421 0.9263158 0.01388889 0.0000000 1.0000000
## 4 0.04347826 0.00000000 0.02083333 0.9791667 0.01388889 0.0000000 0.8333333
## 5 0.08333333 0.00000000 0.05208333 0.9479167 0.00000000 0.0000000 0.7142857
## 6 0.12500000 0.02083333 0.03125000 0.9479167 0.00000000 0.1666667 0.5000000
## L3N_rate L2O_rate L2S_rate L2N_rate L1O_rate L1S_rate L1N_rate
## 1 0.0000000 0.2500000 0.7500000 0.00000000 0.3333333 0.6666667 0.00000000
## 2 0.0000000 0.1666667 0.8333333 0.00000000 0.3636364 0.5454545 0.09090909
## 3 0.0000000 0.1666667 0.8333333 0.00000000 0.3636364 0.5454545 0.09090909
## 4 0.1666667 0.3750000 0.6250000 0.00000000 0.4444444 0.5555556 0.00000000
## 5 0.2857143 0.5000000 0.5000000 0.00000000 0.6363636 0.3636364 0.00000000
## 6 0.3333333 0.3333333 0.5833333 0.08333333 0.5000000 0.5000000 0.00000000
## Average.RT.when.incorrect Lure.Discrimination.Index
## 1 1346.660 0.7288453
## 2 1376.273 0.6654462
## 3 1376.273 0.6654462
## 4 1331.080 0.6313406
## 5 1133.379 0.4479167
## 6 1072.975 0.5104167
## Lure.Discrimination.Index.Lure.Bin.3 Lure.Discrimination.Index.Lure.Bin.2
## 1 0.9462366 0.6962366
## 2 0.9263158 0.7596491
## 3 0.9263158 0.7596491
## 4 0.8125000 0.6041667
## 5 0.6622024 0.4479167
## 6 0.4687500 0.5520833
## Lure.Discrimination.Index.Lure.Bin.1 Pattern.Completion.Rate
## 1 0.6129032 0.1851332
## 2 0.4717703 0.2173913
## 3 0.4717703 0.2173913
## 4 0.5347222 0.3043478
## 5 0.3115530 0.4166667
## 6 0.4687500 0.3125000
## Recognition.Memory cortisol_t1 cortisol_t2 cortisol_t3 SedTimeTypDay
## 1 0.8677419 NA NA NA 480
## 2 0.9166667 NA NA NA 480
## 3 0.9166667 NA NA NA 480
## 4 1.0000000 0.505 0.412 0.484 480
## 5 0.9166667 0.582 0.474 0.376 480
## 6 0.9791667 0.759 0.603 0.470 480
## WalkTimeTotMin ModTimeTotMin VigTimeTotMin Age HtIn HtM WtKg Wtlbs
## 1 30.00000 17.142857 5.00000 25 63.5 1.612903 58.27664 128.5
## 2 30.00000 17.142857 5.00000 25 63.5 1.612903 58.27664 128.5
## 3 30.00000 17.142857 5.00000 25 63.5 1.612903 58.27664 128.5
## 4 25.71429 6.428571 12.85714 21 65.7 1.668783 65.26077 143.9
## 5 25.71429 6.428571 12.85714 21 65.7 1.668783 65.26077 143.9
## 6 25.71429 6.428571 12.85714 21 65.7 1.668783 65.26077 143.9
## BMI Sex English CESDScore Education Race
## 1 22.40325 Female English 5 19 White
## 2 22.40325 Female English 5 19 White
## 3 22.40325 Female English 5 19 White
## 4 23.43610 Female English 1 14 White
## 5 23.43610 Female English 1 14 White
## 6 23.43610 Female English 1 14 White## X Sub_ID Appointment_Number ItemOrdr ItemID Response Score
## 1 1 MAE_001 Appointment_1 1 FLANKER_ARROW_PRAC1 1 1
## 2 2 MAE_001 Appointment_1 2 FLANKER_ARROW_PRAC2 2 1
## 3 3 MAE_001 Appointment_1 3 FLANKER_ARROW_PRAC3 1 1
## 4 4 MAE_001 Appointment_1 4 FLANKER_ARROW_PRAC4 2 1
## 5 5 MAE_001 Appointment_1 1 FLANKER_ARROW_CONGRUENT1 1 1
## 6 6 MAE_001 Appointment_1 2 FLANKER_ARROW_CONGRUENT2 2 1
## ResponseTime DateCreated
## 1 0.558145 2021-11-15 10:13:28
## 2 0.461735 2021-11-15 10:13:34
## 3 0.459106 2021-11-15 10:13:40
## 4 0.432569 2021-11-15 10:13:46
## 5 0.401191 2021-11-15 10:14:01
## 6 0.281966 2021-11-15 10:14:06Data Cleaning
Table 1 - Demographic Data
-Jena Moody’s functions utilized here -Table copied and pasted and then manually formatted in Microsoft Word for final version
| Female (N=9) |
Male (N=9) |
Overall (N=18) |
|
|---|---|---|---|
Sedentary,Walking,Moderate Intensity,Vigorous Intensity time estimates per day were collected as subjective estimates through the IPAQ-SF. Notes: BMI= body mass index; CES-D= Center for Epidemiological Studies Depression Scale. | |||
| Age (years) | |||
| Mean (SD) | 21.1 (2.57) | 22.0 (2.74) | 21.6 (2.62) |
| Education (years) | |||
| Mean (SD) | 15.0 (2.55) | 15.6 (2.74) | 15.3 (2.59) |
| CES-D | |||
| Mean (SD) | 5.44 (3.84) | 7.22 (3.87) | 6.33 (3.85) |
| Height (M) | |||
| Mean (SD) | 1.66 (0.0537) | 1.71 (0.0732) | 1.68 (0.0680) |
| Weight (Kg) | |||
| Mean (SD) | 70.2 (10.7) | 71.8 (11.7) | 71.0 (10.9) |
| BMI (Kg/m^2) | |||
| Mean (SD) | 25.6 (3.62) | 24.8 (5.10) | 25.2 (4.31) |
| Sedentary Time (hours/day) | |||
| Mean (SD) | 7.50 (1.54) | 7.89 (2.85) | 7.69 (2.23) |
| Time Spent Walking (hours/day) | |||
| Mean (SD) | 1.17 (1.18) | 1.18 (1.87) | 1.18 (1.52) |
| Time Spent at Moderate Intensity (hours/day) | |||
| Mean (SD) | 0.288 (0.273) | 0.858 (1.27) | 0.573 (0.936) |
| Time Spent at Vigorous Intensity (hours/day) | |||
| Mean (SD) | 0.332 (0.322) | 0.787 (0.544) | 0.560 (0.493) |
| Race | |||
| Asian | 1 (11.1%) | 4 (44.4%) | 5 (27.8%) |
| Prefer_Not_Say | 1 (11.1%) | 0 (0%) | 1 (5.6%) |
| White | 7 (77.8%) | 5 (55.6%) | 12 (66.7%) |
Table 2 - Exercise Manipulation Summary
-HR continuously collected and RPE collected every min (except for control condition where RPE collected at beginning and end)
-Mean HR/RPE computed during each session for each participant -Mean (SD) then computed across all participants
-Example: Mean of Sub 1 computed during their rest appt (70 BPM; 6 RPE) -Example: Mean and SD of ALL individual rest means computed (HR/RPE) computed
-Table data copied and pasted into Microsoft Word and manually formatted for final version
## [1] 11.2 18.2 18.3## [1] 3.1## Condition Mean Mean RPE Mean Mean HR SD Mean HR
## 1 Control 6 83.25 11.5
## 2 Light Exercise 9.07 110.36 2.96
## 3 Vigorous Exercise 13.27 147.98 3.14
## Mean Percentage of Time in Zone Mean Lower THR Bound Mean Upper THR Bound
## 1 Not Applicable Not Applicable Not Applicable
## 2 0.928 104.56 115.89
## 3 0.906 142.48 153.83
## SD Mean RPE Mean Mean %HRR SD Mean %HRR
## 1 0 13.1 5.49
## 2 0.69 34.61 2.36
## 3 0.84 64.37 2.5Results - Exercise Manipulation
-I have code for One-Way ANOVAs for the main effect of condition on Avg HR/RPE -We chose not to incorporate these results into the paper -Missing data (HR: 3.1, RPE: 11.2, 18.2, 18.3) -Complicated scenario (Participant 16 completed light condition twice) -Assumptions of ANOVA violated -(RPE data severely violates normality assumptions) -(HR data more variable for exercise versus rest)
Results - Continuous MST
-Followed this approach: 1.) Completed ANOVA and Post-Hoc BEFORE verifying assumptions 2.) Verified assumptions and removed outliers (>3 sd from mean) 3.) Re-did ANOVA and Post-Hoc With Outliers removed
-Retained original analysis if outliers didn’t impact results -Primary Outcome Measures: LDI (Lure Bins 1-3)
1.) ANOVA/Post-Hoc
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Condition 2 32 0.022 0.97800000000000 0.000212
## 2 Lure_Similarity 2 32 71.661 0.00000000000152 * 0.327000
## 3 Condition:Lure_Similarity 4 64 0.316 0.86600000000000 0.005000## # A tibble: 9 × 11
## Condition .y. group1 group2 n1 n2 statistic df p p.adj
## * <chr> <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl>
## 1 Control Lure_Disc… High Low 17 17 -6.10 16 1.52e-5 4.56e-5
## 2 Control Lure_Disc… High Medium 17 17 -4.30 16 5.48e-4 2 e-3
## 3 Control Lure_Disc… Low Medium 17 17 1.70 16 1.08e-1 3.24e-1
## 4 Light Lure_Disc… High Low 17 17 -6.95 16 3.26e-6 9.78e-6
## 5 Light Lure_Disc… High Medium 17 17 -5.38 16 6.17e-5 1.85e-4
## 6 Light Lure_Disc… Low Medium 17 17 2.30 16 3.5 e-2 1.05e-1
## 7 Vigorous Lure_Disc… High Low 17 17 -6.17 16 1.35e-5 4.05e-5
## 8 Vigorous Lure_Disc… High Medium 17 17 -3.18 16 6 e-3 1.7 e-2
## 9 Vigorous Lure_Disc… Low Medium 17 17 3.00 16 8 e-3 2.5 e-2
## # ℹ 1 more variable: p.adj.signif <chr>## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 2 32 0.149 0.862 0.0032.) Assumption Verification/Outlier Removal - LDI
LDI: -Normality violated for (Control and Vigorous Low Similarity) -Equal Variance Test not violated -Outlier detected (# 7) and removed
RM: -Normality severely violated -Equal Variance Test not violated -Chose not to perform outlier removal etc. due to severe violation of ANOVA assumptions -Additionally, this wasn’t a primary measure of interest
## Condition Lure_Similarity variable statistic p
## 1 Control High Lure_Discrimination_Index 0.9665915 0.756427913
## 2 Control Low Lure_Discrimination_Index 0.8196430 0.003820651
## 3 Control Medium Lure_Discrimination_Index 0.9385815 0.301749272
## 4 Light High Lure_Discrimination_Index 0.9608603 0.647706289
## 5 Light Low Lure_Discrimination_Index 0.9293440 0.212209676
## 6 Light Medium Lure_Discrimination_Index 0.9506892 0.467511858
## 7 Vigorous High Lure_Discrimination_Index 0.9822780 0.974952592
## 8 Vigorous Low Lure_Discrimination_Index 0.7899678 0.001482829
## 9 Vigorous Medium Lure_Discrimination_Index 0.9408985 0.328995138## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 0.9906 0.4459
## 144## # A tibble: 153 × 5
## Condition Sub_ID Lure_Similarity Lure_Discrimination_Index z_score[,1]
## <chr> <int> <chr> <dbl> <dbl>
## 1 Control 1 Low 0.946 0.661
## 2 Light 1 Low 0.926 0.874
## 3 Vigorous 1 Low 0.926 0.572
## 4 Vigorous 2 Low 0.812 0.0328
## 5 Control 2 Low 0.662 -0.478
## 6 Light 2 Low 0.469 -1.75
## 7 Vigorous 4 Low 0.644 -0.765
## 8 Control 4 Low 0.693 -0.353
## 9 Light 4 Low 0.780 0.0339
## 10 Light 5 Low 0.667 -0.612
## # ℹ 143 more rows## Cond variable statistic p
## 1 Control Recognition.Memory 0.9306179 0.222881793
## 2 Light Recognition.Memory 0.8237508 0.004376191
## 3 Vigorous Recognition.Memory 0.9068220 0.088422079## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 2 0.0293 0.9712
## 483.) ANOVA/Post-Hoc
LDI: -Results unchanged by outlier removal -Initial ANOVA results utilized in manuscript
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Condition 2 30 0.096 0.909000000000000 0.001
## 2 Lure_Similarity 2 30 85.863 0.000000000000385 * 0.377
## 3 Condition:Lure_Similarity 4 60 0.405 0.804000000000000 0.007## # A tibble: 9 × 11
## Condition .y. group1 group2 n1 n2 statistic df p p.adj
## * <chr> <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl>
## 1 Control Lure_Disc… High Low 16 16 -5.76 15 3.73e-5 1.12e-4
## 2 Control Lure_Disc… High Medium 16 16 -3.95 15 1 e-3 4 e-3
## 3 Control Lure_Disc… Low Medium 16 16 1.82 15 8.9 e-2 2.66e-1
## 4 Light Lure_Disc… High Low 16 16 -6.86 15 5.42e-6 1.63e-5
## 5 Light Lure_Disc… High Medium 16 16 -5.38 15 7.6 e-5 2.28e-4
## 6 Light Lure_Disc… Low Medium 16 16 2.15 15 4.8 e-2 1.46e-1
## 7 Vigorous Lure_Disc… High Low 16 16 -9.95 15 5.33e-8 1.6 e-7
## 8 Vigorous Lure_Disc… High Medium 16 16 -3.50 15 3 e-3 1 e-2
## 9 Vigorous Lure_Disc… Low Medium 16 16 3.61 15 3 e-3 8 e-3
## # ℹ 1 more variable: p.adj.signif <chr>4.) Plotting
*LDI versus Condition (Facet wrapped by Lure Similarity)
-outliers greater than 3 sd included in these plots (results not impacted by inclusion) -unadjusted p-values utilized
*LDI versus Lure Similarity (Facet wrapped by Condition)
-outliers greater than 3 sd included in these plots (results not impacted by inclusion) -unadjusted p-values utilized
### *Proportion of Responses
*Saving Plots
5.) Correlations
-Goal of this analysis was to explore correlation between exercise induced changes in LDI -Computed change scores (Vig - Rest, Vig - Light, Light - Rest) and plotted against baseline level of PA
Variables: Overall LDI (across lure bin difficulty) for rest, light, and vigorous conditions, and total IPAQ METs
*Data Cleaning
*Mixed Models (NOT REVIEWED/IN PAPER)
This was exploratory and not reviewed or included in the paper.
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Cond * Lure_Similarity + (1 | Sub_ID)
## Data: B_M_Final
##
## REML criterion at convergence: -82.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.8923 -0.4710 0.0364 0.6785 2.3760
##
## Random effects:
## Groups Name Variance Std.Dev.
## Sub_ID (Intercept) 0.01717 0.1310
## Residual 0.02198 0.1482
## Number of obs: 153, groups: Sub_ID, 17
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 0.455383 0.047987 56.721150 9.490
## CondLight 0.007978 0.050849 128.000000 0.157
## CondVigorous 0.026465 0.050849 128.000000 0.520
## Lure_SimilarityLow 0.326050 0.050849 128.000000 6.412
## Lure_SimilarityMedium 0.243035 0.050849 128.000000 4.780
## CondLight:Lure_SimilarityLow -0.015756 0.071912 128.000000 -0.219
## CondVigorous:Lure_SimilarityLow -0.002326 0.071912 128.000000 -0.032
## CondLight:Lure_SimilarityMedium -0.006844 0.071912 128.000000 -0.095
## CondVigorous:Lure_SimilarityMedium -0.058666 0.071912 128.000000 -0.816
## Pr(>|t|)
## (Intercept) 0.00000000000026 ***
## CondLight 0.876
## CondVigorous 0.604
## Lure_SimilarityLow 0.00000000252654 ***
## Lure_SimilarityMedium 0.00000474225002 ***
## CondLight:Lure_SimilarityLow 0.827
## CondVigorous:Lure_SimilarityLow 0.974
## CondLight:Lure_SimilarityMedium 0.924
## CondVigorous:Lure_SimilarityMedium 0.416
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) CndLgh CndVgr Lr_SmL Lr_SmM CL:L_SL CV:L_SL CL:L_SM
## CondLight -0.530
## CondVigoros -0.530 0.500
## Lr_SmlrtyLw -0.530 0.500 0.500
## Lr_SmlrtyMd -0.530 0.500 0.500 0.500
## CndLgh:L_SL 0.375 -0.707 -0.354 -0.707 -0.354
## CndVgr:L_SL 0.375 -0.354 -0.707 -0.707 -0.354 0.500
## CndLgh:L_SM 0.375 -0.707 -0.354 -0.354 -0.707 0.500 0.250
## CndVgr:L_SM 0.375 -0.354 -0.707 -0.354 -0.707 0.250 0.500 0.500## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Cond * Lure_Similarity * TotPAMET +
## (1 | Sub_ID)
## Data: B_M_Final
##
## REML criterion at convergence: 83.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.89321 -0.49205 0.03367 0.70699 1.98863
##
## Random effects:
## Groups Name Variance Std.Dev.
## Sub_ID (Intercept) 0.01855 0.1362
## Residual 0.02120 0.1456
## Number of obs: 153, groups: Sub_ID, 17
##
## Fixed effects:
## Estimate Std. Error
## (Intercept) 0.59700930 0.09780794
## CondLight -0.14376194 0.10102029
## CondVigorous -0.22544185 0.10102029
## Lure_SimilarityLow 0.27340341 0.10102029
## Lure_SimilarityMedium 0.08580353 0.10102029
## TotPAMET -0.00004098 0.00002460
## CondLight:Lure_SimilarityLow 0.02071101 0.14286426
## CondVigorous:Lure_SimilarityLow 0.18797842 0.14286426
## CondLight:Lure_SimilarityMedium 0.08358703 0.14286426
## CondVigorous:Lure_SimilarityMedium 0.24680769 0.14286426
## CondLight:TotPAMET 0.00004391 0.00002541
## CondVigorous:TotPAMET 0.00007289 0.00002541
## Lure_SimilarityLow:TotPAMET 0.00001523 0.00002541
## Lure_SimilarityMedium:TotPAMET 0.00004550 0.00002541
## CondLight:Lure_SimilarityLow:TotPAMET -0.00001055 0.00003594
## CondVigorous:Lure_SimilarityLow:TotPAMET -0.00005507 0.00003594
## CondLight:Lure_SimilarityMedium:TotPAMET -0.00002617 0.00003594
## CondVigorous:Lure_SimilarityMedium:TotPAMET -0.00008840 0.00003594
## df t value Pr(>|t|)
## (Intercept) 49.23677204 6.104 0.000000159
## CondLight 120.00000038 -1.423 0.15730
## CondVigorous 120.00000035 -2.232 0.02749
## Lure_SimilarityLow 120.00000039 2.706 0.00779
## Lure_SimilarityMedium 120.00000034 0.849 0.39737
## TotPAMET 49.23677192 -1.666 0.10210
## CondLight:Lure_SimilarityLow 120.00000044 0.145 0.88498
## CondVigorous:Lure_SimilarityLow 120.00000041 1.316 0.19075
## CondLight:Lure_SimilarityMedium 120.00000036 0.585 0.55959
## CondVigorous:Lure_SimilarityMedium 120.00000037 1.728 0.08664
## CondLight:TotPAMET 120.00000052 1.728 0.08656
## CondVigorous:TotPAMET 120.00000047 2.869 0.00487
## Lure_SimilarityLow:TotPAMET 120.00000053 0.600 0.54994
## Lure_SimilarityMedium:TotPAMET 120.00000047 1.791 0.07588
## CondLight:Lure_SimilarityLow:TotPAMET 120.00000054 -0.294 0.76953
## CondVigorous:Lure_SimilarityLow:TotPAMET 120.00000050 -1.532 0.12805
## CondLight:Lure_SimilarityMedium:TotPAMET 120.00000046 -0.728 0.46791
## CondVigorous:Lure_SimilarityMedium:TotPAMET 120.00000045 -2.460 0.01532
##
## (Intercept) ***
## CondLight
## CondVigorous *
## Lure_SimilarityLow **
## Lure_SimilarityMedium
## TotPAMET
## CondLight:Lure_SimilarityLow
## CondVigorous:Lure_SimilarityLow
## CondLight:Lure_SimilarityMedium
## CondVigorous:Lure_SimilarityMedium .
## CondLight:TotPAMET .
## CondVigorous:TotPAMET **
## Lure_SimilarityLow:TotPAMET
## Lure_SimilarityMedium:TotPAMET .
## CondLight:Lure_SimilarityLow:TotPAMET
## CondVigorous:Lure_SimilarityLow:TotPAMET
## CondLight:Lure_SimilarityMedium:TotPAMET
## CondVigorous:Lure_SimilarityMedium:TotPAMET *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Age + Sex + BMI + Race + CESDScore +
## Education + Recognition.Memory + Cond * Lure_Similarity + (1 | Sub_ID)
## Data: B_M_Final
##
## REML criterion at convergence: -60.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.76847 -0.52998 0.03857 0.74708 2.41480
##
## Random effects:
## Groups Name Variance Std.Dev.
## Sub_ID (Intercept) 0.007986 0.08936
## Residual 0.022126 0.14875
## Number of obs: 153, groups: Sub_ID, 17
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 1.053850 0.444165 9.903669 2.373
## Age -0.129485 0.050658 8.400202 -2.556
## SexMale -0.021373 0.062536 8.407600 -0.342
## BMI -0.005289 0.006620 8.397530 -0.799
## RacePrefer_Not_Say 0.020500 0.131461 8.294586 0.156
## RaceWhite 0.002478 0.063235 8.336075 0.039
## CESDScore -0.013482 0.008606 8.403718 -1.567
## Education 0.157114 0.051330 8.394262 3.061
## Recognition.Memory 0.025959 0.213849 76.017264 0.121
## CondLight 0.007703 0.051070 126.923860 0.151
## CondVigorous 0.026238 0.051054 126.877764 0.514
## Lure_SimilarityLow 0.326050 0.051020 126.778945 6.391
## Lure_SimilarityMedium 0.243035 0.051020 126.778945 4.764
## CondLight:Lure_SimilarityLow -0.015756 0.072153 126.778945 -0.218
## CondVigorous:Lure_SimilarityLow -0.002326 0.072153 126.778945 -0.032
## CondLight:Lure_SimilarityMedium -0.006844 0.072153 126.778945 -0.095
## CondVigorous:Lure_SimilarityMedium -0.058666 0.072153 126.778945 -0.813
## Pr(>|t|)
## (Intercept) 0.0393 *
## Age 0.0326 *
## SexMale 0.7409
## BMI 0.4464
## RacePrefer_Not_Say 0.8798
## RaceWhite 0.9697
## CESDScore 0.1540
## Education 0.0147 *
## Recognition.Memory 0.9037
## CondLight 0.8803
## CondVigorous 0.6082
## Lure_SimilarityLow 0.00000000287 ***
## Lure_SimilarityMedium 0.00000511572 ***
## CondLight:Lure_SimilarityLow 0.8275
## CondVigorous:Lure_SimilarityLow 0.9743
## CondLight:Lure_SimilarityMedium 0.9246
## CondVigorous:Lure_SimilarityMedium 0.4177
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Age + Sex + BMI + Race + CESDScore +
## Education + Recognition.Memory + Cond * Lure_Similarity *
## TotPAMET + (1 | Sub_ID)
## Data: B_M_Final
##
## REML criterion at convergence: 104.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.76100 -0.48986 -0.00035 0.61738 2.04367
##
## Random effects:
## Groups Name Variance Std.Dev.
## Sub_ID (Intercept) 0.008516 0.09228
## Residual 0.021362 0.14616
## Number of obs: 153, groups: Sub_ID, 17
##
## Fixed effects:
## Estimate Std. Error
## (Intercept) 1.28754351 0.49107427
## Age -0.14740843 0.05692462
## SexMale -0.00357848 0.06792016
## BMI -0.00581527 0.00678042
## RacePrefer_Not_Say 0.02581871 0.13458752
## RaceWhite 0.02523261 0.07150212
## CESDScore -0.01777922 0.01085285
## Education 0.17291506 0.05637730
## Recognition.Memory 0.04945819 0.21853287
## CondLight -0.14610172 0.10192864
## CondVigorous -0.22549902 0.10140330
## Lure_SimilarityLow 0.27340341 0.10140298
## Lure_SimilarityMedium 0.08580353 0.10140298
## TotPAMET -0.00002662 0.00002481
## CondLight:Lure_SimilarityLow 0.02071101 0.14340548
## CondVigorous:Lure_SimilarityLow 0.18797842 0.14340548
## CondLight:Lure_SimilarityMedium 0.08358703 0.14340548
## CondVigorous:Lure_SimilarityMedium 0.24680769 0.14340548
## CondLight:TotPAMET 0.00004443 0.00002561
## CondVigorous:TotPAMET 0.00007279 0.00002551
## Lure_SimilarityLow:TotPAMET 0.00001523 0.00002551
## Lure_SimilarityMedium:TotPAMET 0.00004550 0.00002551
## CondLight:Lure_SimilarityLow:TotPAMET -0.00001055 0.00003607
## CondVigorous:Lure_SimilarityLow:TotPAMET -0.00005507 0.00003607
## CondLight:Lure_SimilarityMedium:TotPAMET -0.00002617 0.00003607
## CondVigorous:Lure_SimilarityMedium:TotPAMET -0.00008840 0.00003607
## df t value Pr(>|t|)
## (Intercept) 9.50662948 2.622 0.02654 *
## Age 7.56387117 -2.590 0.03367 *
## SexMale 7.58226205 -0.053 0.95934
## BMI 7.64865252 -0.858 0.41714
## RacePrefer_Not_Say 7.59465530 0.192 0.85290
## RaceWhite 7.54653755 0.353 0.73382
## CESDScore 7.86619628 -1.638 0.14065
## Education 7.57090577 3.067 0.01648 *
## Recognition.Memory 74.91730511 0.226 0.82157
## CondLight 119.69135611 -1.433 0.15436
## CondVigorous 119.05454946 -2.224 0.02805 *
## Lure_SimilarityLow 119.05415864 2.696 0.00803 **
## Lure_SimilarityMedium 119.05415864 0.846 0.39916
## TotPAMET 26.62761730 -1.073 0.29280
## CondLight:Lure_SimilarityLow 119.05415860 0.144 0.88541
## CondVigorous:Lure_SimilarityLow 119.05415858 1.311 0.19244
## CondLight:Lure_SimilarityMedium 119.05415860 0.583 0.56108
## CondVigorous:Lure_SimilarityMedium 119.05415857 1.721 0.08784 .
## CondLight:TotPAMET 119.56476650 1.735 0.08533 .
## CondVigorous:TotPAMET 119.07642872 2.853 0.00511 **
## Lure_SimilarityLow:TotPAMET 119.05415854 0.597 0.55145
## Lure_SimilarityMedium:TotPAMET 119.05415853 1.784 0.07700 .
## CondLight:Lure_SimilarityLow:TotPAMET 119.05415853 -0.293 0.77038
## CondVigorous:Lure_SimilarityLow:TotPAMET 119.05415852 -1.527 0.12950
## CondLight:Lure_SimilarityMedium:TotPAMET 119.05415853 -0.725 0.46960
## CondVigorous:Lure_SimilarityMedium:TotPAMET 119.05415851 -2.451 0.01572 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lure_Discrimination_Index ~ Age + Sex + BMI + Race + CESDScore +
## Education + Recognition.Memory + Cond * Lure_Similarity *
## TotPAMET_zcat + (1 | Sub_ID)
## Data: B_M_Final
##
## REML criterion at convergence: -33.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.80988 -0.52129 0.04966 0.59092 2.26148
##
## Random effects:
## Groups Name Variance Std.Dev.
## Sub_ID (Intercept) 0.005157 0.07181
## Residual 0.022616 0.15039
## Number of obs: 153, groups: Sub_ID, 17
##
## Fixed effects:
## Estimate
## (Intercept) 1.111593
## Age -0.178911
## SexMale -0.041418
## BMI -0.005683
## RacePrefer_Not_Say -0.007113
## RaceWhite 0.029275
## CESDScore -0.012979
## Education 0.210929
## Recognition.Memory 0.191490
## CondLight -0.180071
## CondVigorous -0.135857
## Lure_SimilarityLow 0.333333
## Lure_SimilarityMedium 0.136905
## TotPAMET_zcat> 1 -0.042573
## TotPAMET_zcatBetween -1 and 1 0.064317
## CondLight:Lure_SimilarityLow 0.060606
## CondVigorous:Lure_SimilarityLow 0.049784
## CondLight:Lure_SimilarityMedium 0.120671
## CondVigorous:Lure_SimilarityMedium -0.015693
## CondLight:TotPAMET_zcat> 1 0.288660
## CondVigorous:TotPAMET_zcat> 1 0.324562
## CondLight:TotPAMET_zcatBetween -1 and 1 0.191362
## CondVigorous:TotPAMET_zcatBetween -1 and 1 0.146443
## Lure_SimilarityLow:TotPAMET_zcat> 1 0.018182
## Lure_SimilarityMedium:TotPAMET_zcat> 1 0.159055
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 -0.014863
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.110588
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1 -0.001347
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1 -0.177393
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1 -0.093158
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1 -0.302393
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 -0.107843
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 -0.029473
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 -0.157356
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.014719
## Std. Error
## (Intercept) 0.429549
## Age 0.049452
## SexMale 0.059455
## BMI 0.005855
## RacePrefer_Not_Say 0.113743
## RaceWhite 0.056328
## CESDScore 0.008614
## Education 0.050910
## Recognition.Memory 0.227269
## CondLight 0.151527
## CondVigorous 0.150488
## Lure_SimilarityLow 0.150385
## Lure_SimilarityMedium 0.150385
## TotPAMET_zcat> 1 0.163634
## TotPAMET_zcatBetween -1 and 1 0.139601
## CondLight:Lure_SimilarityLow 0.212677
## CondVigorous:Lure_SimilarityLow 0.212677
## CondLight:Lure_SimilarityMedium 0.212677
## CondVigorous:Lure_SimilarityMedium 0.212677
## CondLight:TotPAMET_zcat> 1 0.195635
## CondVigorous:TotPAMET_zcat> 1 0.194308
## CondLight:TotPAMET_zcatBetween -1 and 1 0.163308
## CondVigorous:TotPAMET_zcatBetween -1 and 1 0.162464
## Lure_SimilarityLow:TotPAMET_zcat> 1 0.194146
## Lure_SimilarityMedium:TotPAMET_zcat> 1 0.194146
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 0.162434
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.162434
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1 0.274564
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1 0.274564
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1 0.274564
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1 0.274564
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 0.229717
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 0.229717
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.229717
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.229717
## df
## (Intercept) 8.802617
## Age 5.775916
## SexMale 5.678353
## BMI 5.657853
## RacePrefer_Not_Say 5.747884
## RaceWhite 5.672051
## CESDScore 6.438600
## Education 5.794539
## Recognition.Memory 64.033989
## CondLight 110.923092
## CondVigorous 110.048060
## Lure_SimilarityLow 109.958364
## Lure_SimilarityMedium 109.958364
## TotPAMET_zcat> 1 38.920316
## TotPAMET_zcatBetween -1 and 1 33.111942
## CondLight:Lure_SimilarityLow 109.958364
## CondVigorous:Lure_SimilarityLow 109.958364
## CondLight:Lure_SimilarityMedium 109.958364
## CondVigorous:Lure_SimilarityMedium 109.958364
## CondLight:TotPAMET_zcat> 1 110.932444
## CondVigorous:TotPAMET_zcat> 1 110.067688
## CondLight:TotPAMET_zcatBetween -1 and 1 110.648982
## CondVigorous:TotPAMET_zcatBetween -1 and 1 109.982006
## Lure_SimilarityLow:TotPAMET_zcat> 1 109.958364
## Lure_SimilarityMedium:TotPAMET_zcat> 1 109.958364
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 109.958364
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 109.958364
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1 109.958364
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1 109.958364
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1 109.958364
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1 109.958364
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 109.958364
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 109.958364
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 109.958364
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 109.958364
## t value
## (Intercept) 2.588
## Age -3.618
## SexMale -0.697
## BMI -0.971
## RacePrefer_Not_Say -0.063
## RaceWhite 0.520
## CESDScore -1.507
## Education 4.143
## Recognition.Memory 0.843
## CondLight -1.188
## CondVigorous -0.903
## Lure_SimilarityLow 2.217
## Lure_SimilarityMedium 0.910
## TotPAMET_zcat> 1 -0.260
## TotPAMET_zcatBetween -1 and 1 0.461
## CondLight:Lure_SimilarityLow 0.285
## CondVigorous:Lure_SimilarityLow 0.234
## CondLight:Lure_SimilarityMedium 0.567
## CondVigorous:Lure_SimilarityMedium -0.074
## CondLight:TotPAMET_zcat> 1 1.476
## CondVigorous:TotPAMET_zcat> 1 1.670
## CondLight:TotPAMET_zcatBetween -1 and 1 1.172
## CondVigorous:TotPAMET_zcatBetween -1 and 1 0.901
## Lure_SimilarityLow:TotPAMET_zcat> 1 0.094
## Lure_SimilarityMedium:TotPAMET_zcat> 1 0.819
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 -0.092
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.681
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1 -0.005
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1 -0.646
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1 -0.339
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1 -1.101
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 -0.469
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 -0.128
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 -0.685
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.064
## Pr(>|t|)
## (Intercept) 0.02983 *
## Age 0.01188 *
## SexMale 0.51352
## BMI 0.37134
## RacePrefer_Not_Say 0.95226
## RaceWhite 0.62291
## CESDScore 0.17925
## Education 0.00653 **
## Recognition.Memory 0.40261
## CondLight 0.23722
## CondVigorous 0.36862
## Lure_SimilarityLow 0.02871 *
## Lure_SimilarityMedium 0.36462
## TotPAMET_zcat> 1 0.79610
## TotPAMET_zcatBetween -1 and 1 0.64801
## CondLight:Lure_SimilarityLow 0.77620
## CondVigorous:Lure_SimilarityLow 0.81536
## CondLight:Lure_SimilarityMedium 0.57160
## CondVigorous:Lure_SimilarityMedium 0.94131
## CondLight:TotPAMET_zcat> 1 0.14291
## CondVigorous:TotPAMET_zcat> 1 0.09769 .
## CondLight:TotPAMET_zcatBetween -1 and 1 0.24380
## CondVigorous:TotPAMET_zcatBetween -1 and 1 0.36935
## Lure_SimilarityLow:TotPAMET_zcat> 1 0.92556
## Lure_SimilarityMedium:TotPAMET_zcat> 1 0.41441
## Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 0.92726
## Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.49742
## CondLight:Lure_SimilarityLow:TotPAMET_zcat> 1 0.99610
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcat> 1 0.51957
## CondLight:Lure_SimilarityMedium:TotPAMET_zcat> 1 0.73504
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcat> 1 0.27315
## CondLight:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 0.63967
## CondVigorous:Lure_SimilarityLow:TotPAMET_zcatBetween -1 and 1 0.89814
## CondLight:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.49478
## CondVigorous:Lure_SimilarityMedium:TotPAMET_zcatBetween -1 and 1 0.94903
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
*Run correlation for light - rest vs. Total METS
##
## Pearson's product-moment correlation
##
## data: B_M_Wide_JS$LDI_Light_Rest and B_M_Wide_JS$TotPAMET
## t = 2.1409, df = 15, p-value = 0.04912
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.004086662 0.782478618
## sample estimates:
## cor
## 0.4837812*Plot
*Run correlation for vigorous - rest vs. Total METS
##
## Pearson's product-moment correlation
##
## data: B_M_Wide_JS$LDI_Vig_Rest and B_M_Wide_JS$TotPAMET
## t = 1.9334, df = 15, p-value = 0.07228
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.04328711 0.76340692
## sample estimates:
## cor
## 0.4466505*Plot
### *Saving Plots
Results - gradCPT
1.) ANOVA/Post-Hoc
-all participants expect #10 kept -Participant 16 completed 2 light appointments due to MST software malfunction. -First light appointment included below since gradCPT data was collected with no issues.
*dprime
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 2 34 4.58 0.017 * 0.074## # A tibble: 3 × 10
## .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 dprime Control Light 18 18 -2.56 17 0.02 0.061 ns
## 2 dprime Control Vigorous 18 18 -2.08 17 0.053 0.159 ns
## 3 dprime Light Vigorous 18 18 0.965 17 0.348 1 ns*Criterion
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 2 34 3.1 0.058 0.059## # A tibble: 3 × 10
## .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 criterion Control Light 18 18 2.58 17 0.019 0.058 ns
## 2 criterion Control Vigoro… 18 18 1.40 17 0.178 0.534 ns
## 3 criterion Light Vigoro… 18 18 -0.931 17 0.365 1 ns*Commission Rate
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 2 34 7.277 0.002 * 0.099## # A tibble: 3 × 10
## .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 commission… Contr… Light 18 18 3.15 17 0.006 0.017 *
## 2 commission… Contr… Vigor… 18 18 2.52 17 0.022 0.066 ns
## 3 commission… Light Vigor… 18 18 -1.33 17 0.2 0.6 ns*Omission Rate
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 1.16 19.68 0.689 0.437 0.023## # A tibble: 3 × 10
## .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 omission_r… Contr… Light 18 18 8.85e- 1 17 0.388 1 ns
## 2 omission_r… Contr… Vigor… 18 18 8.23e- 1 17 0.422 1 ns
## 3 omission_r… Light Vigor… 18 18 1.01e-15 17 1 1 ns*CV RT
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 2 34 2.621 0.087 0.051## # A tibble: 3 × 10
## .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 CV_RT Control Light 18 18 1.20 17 0.246 0.738 ns
## 2 CV_RT Control Vigorous 18 18 2.20 17 0.042 0.125 ns
## 3 CV_RT Light Vigorous 18 18 1.13 17 0.275 0.825 ns2.) Assumption Verification
*dprime
## Cond variable statistic p
## 1 Control dprime 0.8971030 0.05116676
## 2 Light dprime 0.9457116 0.36175115
## 3 Vigorous dprime 0.9419760 0.31313586## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 2 0.2469 0.7822
## 51*Criterion
## Cond variable statistic p
## 1 Control criterion 0.9362474 0.2496984
## 2 Light criterion 0.9637425 0.6751546
## 3 Vigorous criterion 0.9275668 0.1759388## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 2 1.1334 0.3299
## 51*Commission Rate
## Cond variable statistic p
## 1 Control commission_rate 0.9129409 0.09695558
## 2 Light commission_rate 0.9176046 0.11724118
## 3 Vigorous commission_rate 0.9313985 0.20549099## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 2 1.4729 0.2389
## 51*Omission Rate
## Cond variable statistic p
## 1 Control omission_rate 0.4091816 0.0000001433315
## 2 Light omission_rate 0.7224223 0.0001473112217
## 3 Vigorous omission_rate 0.7795962 0.0007933692239## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 2 0.6207 0.5416
## 51*CV RT
## Cond variable statistic p
## 1 Control CV_RT 0.9400147 0.2899536
## 2 Light CV_RT 0.9160026 0.1098295
## 3 Vigorous CV_RT 0.9230854 0.1466036## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 2 0.0426 0.9584
## 514.) Transformation/Outlier Removal
-Transformed omission rate (due to non-normality) -Checked for outliers
## [1] 5.582044## [1] 0.9177454## [1] NaN## [1] 1.650815## [1] 5.579035## [1] 0.667746## $Sub_ID
## integer(0)
##
## $Sub_ID
## integer(0)
##
## $Sub_ID
## integer(0)
##
## $Sub_ID
## integer(0)
##
## $Sub_ID
## integer(0)5.) ANOVA/Post-Hoc
*dprime
-No need to re-run as no outliers detected/no violations of ANOVA assumptions.
*Criterion
-No need to re-run as no outliers detected/no violations of ANOVA assumptions.
*Commission Rate
-No need to re-run as no outliers detected/no violations of ANOVA assumptions.
*Omission Rate
-Re-ran after normality improved
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 2 34 0.073 0.93 0.002## # A tibble: 3 × 10
## .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 omission_r… Contr… Light 18 18 0.379 17 0.709 1 ns
## 2 omission_r… Contr… Vigor… 18 18 0.106 17 0.917 1 ns
## 3 omission_r… Light Vigor… 18 18 -0.266 17 0.793 1 ns*CV RT
-No need to re-run as no outliers detected/no violations of ANOVA assumptions.
6.) Plotting
-ggboxplot utilizes 1.5*IQR as outlier criteria -This means some outliers on the plots do not match our outlier criteria (M +- 3sd) -Noted in figure captions
*dprime
## # A tibble: 3 × 8
## .y. group1 group2 p p.adj p.format p.signif method
## <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
## 1 dprime Control Light 0.0204 0.02 0.020 * T-test
## 2 dprime Control Vigorous 0.0530 0.053 0.053 p = .053 T-test
## 3 dprime Light Vigorous 0.348 0.35 0.348 ns T-test
*criterion
*Commission Rate
*Omission Rate
*CV RT
*Saving
Results - Facename Task
-Note, there was an issue with the stimulus presentation for FN task -This hasn’t been reviewed/isn’t published
1.) ANOVA/Post-Hoc
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 1.46 21.83 0.477 0.567 0.016## # A tibble: 3 × 10
## .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 Accuracy_R… Contr… Light 16 16 -0.152 15 0.881 1 ns
## 2 Accuracy_R… Contr… Vigor… 16 16 -0.765 15 0.456 1 ns
## 3 Accuracy_R… Light Vigor… 16 16 -1.17 15 0.258 0.774 ns2.) Assumption Verification
-recall, participants performed near ceiling on this task
## Cond variable statistic p
## 1 Control Accuracy_Response_Trials 0.8516442 0.014406092
## 2 Light Accuracy_Response_Trials 0.8006635 0.002779345
## 3 Vigorous Accuracy_Response_Trials 0.9269438 0.217977871## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 2 2.87 0.06713 .
## 45
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 13.) Transformation/Outlier Removal
## # A tibble: 0 × 1
## # ℹ 1 variable: Sub_ID <int>## [1] -1.559713## [1] -2.082307## [1] -1.81003## [1] -1.951025## [1] -1.89841## [1] -0.98001154.) ANOVA/Post-Hoc
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 2 30 0.331 0.721 0.011## # A tibble: 3 × 10
## .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 transforme… Contr… Light 16 16 0.0301 15 0.976 1 ns
## 2 transforme… Contr… Vigor… 16 16 -0.577 15 0.573 1 ns
## 3 transforme… Light Vigor… 16 16 -1.08 15 0.297 0.891 ns5.) Plotting
*Accuracy Response Trials
-Significance and data non-transformed here (doesn’t matter as
P-Values non-significant for both)
*Saving
Results - Flanker Task
1.) ANOVA/Post-Hoc
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 Cond 2 34 0.306 0.738 0.005## # A tibble: 3 × 10
## .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 Age.Correc… Contr… Light 18 18 -0.215 17 0.832 1 ns
## 2 Age.Correc… Contr… Vigor… 18 18 -1.14 17 0.272 0.816 ns
## 3 Age.Correc… Light Vigor… 18 18 -0.465 17 0.648 1 ns2.) Assumption Verification
## Cond variable statistic p
## 1 Control Age.Corrected.Standard.Score 0.9527735 0.47016698
## 2 Light Age.Corrected.Standard.Score 0.9505375 0.43351143
## 3 Vigorous Age.Corrected.Standard.Score 0.8669769 0.01587097## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 2 0.0556 0.946
## 513.) Transformation/Outlier Removal
-1 sd is 15 so 3d=45 -100 plus and minus 45 is 3 sd
## [1] -0.7015437## integer(0)## integer(0)4.) ANOVA/Post-Hoc
-No need to re-run as not severely skewed/no violation Levene’s test.
5.) Plotting
*Age Corrected Standard Scores
*Saving Plot
Results - Cortisol
1.) Exploration
-Participants provided three samples (pre-exercise, post-exercise, end of appt)
-2 data forms cleaned and explored: Absolute (T1, T2, T3) Relative (T2-T1, T3-T1, T3-T2)
2.) Plotting
*individual lines
*suplemental appendix draft (with error bars)
*suplemental appendix (actual)
3.) ANOVA/Post-Hoc
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 timepoint 1.50 23.98 12.929 0.000428 * 0.059
## 2 Cond 2.00 32.00 0.878 0.426000 0.015
## 3 timepoint:Cond 2.75 44.05 1.372 0.264000 0.007## # A tibble: 9 × 11
## Cond .y. group1 group2 n1 n2 statistic df p p.adj
## * <chr> <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl>
## 1 Control cortisol cortisol… corti… 17 17 -0.00982 16 9.92e-1 9.92e-1
## 2 Control cortisol cortisol… corti… 17 17 4.68 16 2.54e-4 2.54e-4
## 3 Control cortisol cortisol… corti… 17 17 2.88 16 1.1 e-2 1.1 e-2
## 4 Light cortisol cortisol… corti… 17 17 2.43 16 2.7 e-2 2.7 e-2
## 5 Light cortisol cortisol… corti… 17 17 4.12 16 8.03e-4 8.03e-4
## 6 Light cortisol cortisol… corti… 17 17 4.58 16 3.1 e-4 3.1 e-4
## 7 Vigorous cortisol cortisol… corti… 17 17 -0.644 16 5.29e-1 5.29e-1
## 8 Vigorous cortisol cortisol… corti… 17 17 1.30 16 2.11e-1 2.11e-1
## 9 Vigorous cortisol cortisol… corti… 17 17 2.13 16 4.9 e-2 4.9 e-2
## # ℹ 1 more variable: p.adj.signif <chr>4.) Assumption Verification
## Cond timepoint variable statistic p
## 1 Control cortisol_t1 cortisol 0.9613664 0.657293055
## 2 Control cortisol_t2 cortisol 0.8307220 0.005525197
## 3 Control cortisol_t3 cortisol 0.9689943 0.800581219
## 4 Light cortisol_t1 cortisol 0.9343070 0.256702691
## 5 Light cortisol_t2 cortisol 0.9149377 0.121239384
## 6 Light cortisol_t3 cortisol 0.9163350 0.128023258
## 7 Vigorous cortisol_t1 cortisol 0.9750651 0.899415419
## 8 Vigorous cortisol_t2 cortisol 0.9533288 0.511243184
## 9 Vigorous cortisol_t3 cortisol 0.9449839 0.382146307## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 1.4037 0.1997
## 1445.) ANOVA/Post-Hoc
## ANOVA Table (type III tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 timepoint 1.33 19.90 11.394 0.002 * 0.055
## 2 Cond 2.00 30.00 1.704 0.199 0.030
## 3 timepoint:Cond 2.35 35.28 1.849 0.167 0.007## # A tibble: 9 × 11
## Cond .y. group1 group2 n1 n2 statistic df p p.adj
## * <chr> <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl>
## 1 Control cortisol cortisol… corti… 16 16 3.36 15 4 e-3 4 e-3
## 2 Control cortisol cortisol… corti… 16 16 4.57 15 3.67e-4 3.67e-4
## 3 Control cortisol cortisol… corti… 16 16 3.69 15 2 e-3 2 e-3
## 4 Light cortisol cortisol… corti… 16 16 2.08 15 5.5 e-2 5.5 e-2
## 5 Light cortisol cortisol… corti… 16 16 3.86 15 2 e-3 2 e-3
## 6 Light cortisol cortisol… corti… 16 16 4.28 15 6.64e-4 6.64e-4
## 7 Vigorous cortisol cortisol… corti… 16 16 -0.900 15 3.82e-1 3.82e-1
## 8 Vigorous cortisol cortisol… corti… 16 16 1.09 15 2.91e-1 2.91e-1
## 9 Vigorous cortisol cortisol… corti… 16 16 2.02 15 6.2 e-2 6.2 e-2
## # ℹ 1 more variable: p.adj.signif <chr>